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Optimising pharmacy input to medicines reconciliation at admission to hospital: lessons from a collaborative service evaluation of pharmacy-led medicines reconciliation services in 30 acute hospitals in England
  1. Linda J Dodds
  1. Correspondence to Linda J Dodds, Medicines Use and Safety Division, East and South East England Specialist Pharmacy Services, Clinical Pharmacy Unit, Northwick Park Hospital, Watford Road, Harrow HA1 3UJ, UK; Linda.Dodds{at}nhs.net

Abstract

Objective To compare pharmacy team input to medicines reconciliation (MR) in a variety of care areas in order to inform optimisation of service delivery.

Methods 30 acute hospital pharmacy departments evaluated their MR services in 10 care areas using a piloted data collection form. Omitted medicines and wrong dose discrepancies on the admission prescription were recorded and rated for clinical severity. Data were collected on whether the admission was planned, the number of coprescribed medicines and if the patient had brought their home medicines into hospital.

Results 3086 MRs were reviewed and 4041 unintended discrepancies (UDs) in prescribing were identified (mean 1.3/MR). 1616 UDs (0.52 per patient) were ranked as having the potential for moderate impact on patient care (Level 3). Level 3 UDs were identified in all care areas; however, Admissions, Care of the Elderly, General Surgery and Orthopaedic patients had more Level 3 UDs per patient than the total population (two-tailed Z test, 99% CI). More UDs was ranked Level 3 in Care of the Elderly and General Surgery patients (two-tailed Z test, 99% CI). Over 80% of recorded errors involved four prescribing categories (cardiovascular, central nervous system, endocrine, respiratory). Planned admissions and the presence of the patients’ own medicines had little impact on the accuracy of admission prescribing. The average time to carry out MR was 15 min.

Conclusions Prioritisation of pharmacy-led MR by care area or type of admission alone is not a safe option. Opportunities should instead be taken to explore multidisciplinary methods of implementing MR which optimise available information.

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